Communitygithub.com

amplitude/builder-skills

當用戶想要在競爭對手目前主導的提示詞上贏得 AI 引用時使用此技能——無論他們是說「競爭對手比我們更常被引用」、「我們在這些提示詞上輸了」、「我要如何超越[競爭對手]的 AI 回答」、「找出我們應該贏的提示詞」、「建立內容來擊敗[競爭對手]」,或任何以搶回競爭對手目前擁有的提示詞 AI 佔有率為目標的變體。此技能會從 AI Visibility 拉取競爭對手的可見度資料,識別競爭對手獲勝而 Amplitude 缺席的特定提示詞,按意圖進行分組,並產出有針對性的比較頁面、替代方案內容或反擊素材——然後將草稿推送到 CMS。在提及競爭對手、提示詞劫持、超越排名或「為什麼[競爭對手]比我們更常被引用」時觸發。

builder-skills 是什麼?

這項技能專為內容團隊設計,幫助他們從競爭對手手中奪回 AI 引用。當 AI 模型被問到「最好的產品分析工具是什麼」或「Mixpanel vs Amplitude」時,其回答取決於現有內容。此技能會找出每個競爭對手勝出而 Amplitude 缺席的提示詞,並產出專為翻轉這些引用而設計的內容。 該技能支援 Amplitude 的內容行銷流程,並與多個 CMS 平台整合,包括 Sanity、Contentful、HubSpot、WordPress、Ghost 和 Webflow。工作流程從 CMS 探索開始,接著識別品牌並拉取競爭對手格局,再找出競爭對手勝出的提示詞,按意圖分組(直接比較、替代方案、類別佔領),診斷競爭對手的說詞,產出針對性的比較頁面、替代方案或類別佔領內容,最後將草稿推送到 CMS。 此技能適用於 Claude Code、Coda 以及支援 AI Visibility API 和 CMS 工具連線的通用 AI 代理。它利用 AI Visibility 平台的資料,包括組織品牌、競爭對手、提示詞和頁面端點,以及網頁擷取功能。關鍵優點包括:系統性地識別 AI 引用缺口、根據實際 AI 回應產生內容、直接推送到 CMS 避免複製貼上,以及提供可翻轉引用說詞的結構化指南。

相容平台~Claude Code~Codex CLI~Cursor
npx skills add https://github.com/amplitude/builder-skills/tree/HEAD/content-marketing-skills/skills/competitor-prompt-hijacker

在你喜歡的 AI 中提問

開啟一個已預先載入此 Agent Skill 的新對話。

說明文件

競爭對手提示詞劫持者

你正在協助內容團隊從競爭對手手中奪回 AI 引用。當 AI 模型被問到 「最好的產品分析工具是什麼」或「Mixpanel vs Amplitude」時,其回答取決於現有的書面內容。此技能會找出每個競爭對手勝出而 Amplitude 缺席的提示詞——並產出專門設計來翻轉這些引用的內容。


步驟 0 — CMS 探索(每次工作階段開始時執行一次)

在執行任何其他操作之前,先確認修改後的內容會落在哪裡。這可以避免工作流程結束時出現複製貼上的死胡同。

檢查是否已有連接的 CMS 工具

掃描你環境中目前可用的工具。已知的 CMS MCP 模式:

CMS要查找的工具名稱模式
Sanitysanity, create_documents_from_markdown, patch_document_from_markdown
Contentfulcontentful, create_entry, update_entry
HubSpot CMShubspot, update_blog_post, create_blog_post
WordPresswordpress, wp_update_post, wp_create_post
Ghostghost, update_post, create_post
Webflowwebflow, update_cms_item, create_cms_item

如果已有 CMS MCP 連接: 用一句話確認: 「我看到 [CMS] 已連接——完成後我會將新內容以草稿形式推送到那裡。聽起來不錯吧?」 然後繼續執行步驟 1。

如果沒有任何東西連接: 簡潔地詢問一次:

「在開始之前——您發布到哪個 CMS?我可以直接將內容以草稿形式推送到那裡,而不是交給您一段需要貼上的文字。」

提供選項:Sanity · Contentful · HubSpot · WordPress · Webflow · Ghost · 其他 · 「只要給我內容」

然後根據他們的回答提供量身訂做的設定建議(與 prompt-gap-to-publish 中的指導相同)。不要為了設定而卡住——立即開始分析,並說明等他們連接好時你就準備好推送了。


步驟 1 — 識別品牌並拉取競爭對手格局

使用 list_ai_visibility_org_brands 來識別品牌(或使用用戶指定的品牌)。

然後使用選定的 orgBrandId 呼叫 get_ai_visibility_competitors。這會傳回完整的競爭對手清單,包含欄位:brandId、brandName、brandUrl、visibility、avgRank。

按 visibility 降序排序。可見度最高的競爭對手就是最積極贏得本應屬於 Amplitude 的引用的那些。

列出一個快速表格來引導用戶:

競爭對手可見度 %平均排名
Google Analytics 446%2.1
Mixpanel34%2.8
...

如果用戶已經指定了特定競爭對手,就使用該競爭對手並跳過選擇步驟。否則詢問:「您想先對付哪個競爭對手?」


步驟 2 — 找出競爭對手勝出的提示詞

使用 orgBrandId 呼叫 get_ai_visibility_prompts。對於每個提示詞,你需要了解:

  • 目標競爭對手在此提示詞上的可見度有多高?
  • Amplitude 在此提示詞上的可見度有多高?

尋找符合以下條件的提示詞:

  • 競爭對手可見度高(超過 50%)且 Amplitude 可見度低(低於 30%)
  • 提示詞有較高的 responseCount——更多 AI 回答意味著更多引用機會
  • 提示詞意圖是 Amplitude 應該能合理獲勝的(而不是「如何使用 Google Analytics」)

同時為最弱的 5-10 個提示詞呼叫 get_ai_visibility_prompt_responses。閱讀實際的 LLM 回應可以讓你確切了解 AI 模型目前說什麼——以及你需要反制的語言、框架和主張。


步驟 3 — 按意圖對提示詞進行分組

將識別出的提示詞分成三個群組。這些群組直接對應到內容類型:

群組 1:直接比較 — 像是「[競爭對手] vs Amplitude」、「Amplitude 或 [競爭對手]」、「哪個比較好 [競爭對手] 或 Amplitude」的提示詞。這些需要一個專門的比較頁面,公平地涵蓋兩個工具,並針對特定使用案例做出明確建議。

群組 2:替代方案與發現 — 像是「[競爭對手] 的替代方案」、「[競爭對手] 的競爭對手」、「像 [競爭對手] 的工具」、「最佳 [競爭對手] 替代品」的提示詞。這些需要一個清單文章或替代方案頁面,將 Amplitude 定位為首選推薦。

群組 3:類別佔領 — 像是「最好的產品分析工具」、「頂級數位分析平台」、「我應該用什麼來取代 GA4」的提示詞。即使 Amplitude 直接相關,它卻從 AI 回答中缺席。這些需要一個新的類別頁面或升級現有頁面。

呈現群組細分:

群組# 提示詞範例提示詞Amplitude 可見度競爭對手可見度
直接比較8"Mixpanel vs Amplitude"42%71%
替代方案5"Mixpanel alternatives"18%0%
類別佔領12"best product analytics"29%55%

詢問:「您想先攻擊哪個群組——直接比較、替代方案,還是類別佔領?」 等待他們選擇,或者如果他們想要你的建議,就建議總回應數最高的那個。


步驟 4 — 診斷競爭對手在說什麼

使用 web_fetch 獲取所選群組中排名最高的競爭對手頁面的實際內容。如果從資料中無法識別競爭對手頁面,請使用步驟 2 的 LLM 回應來了解正在提出的主張。

同時使用 get_ai_visibility_pages 搭配 mentionsBrandId(針對該競爭對手)並過濾到 amplitude.com 網域,來拉取 Amplitude 在此主題上的任何現有頁面。

比較:

競爭對手提出而 Amplitude 沒有反駁的主張:逐一列出。這些是需要填補的差距。

競爭對手擁有的框架優勢:例如,「Mixpanel 以『專為產品團隊打造』領先」而 Amplitude 的頁面很籠統。具體的框架勝過籠統的。

競爭對手回答而 Amplitude 頁面沒有回答的問題:從實際的 LLM 回應中提取——AI 回答說了什麼 Amplitude 的內容沒有處理的?

缺少的證明點:定價透明度、整合清單、客戶群體、遷移指南、效能基準。

在撰寫任何內容之前,用 4-6 個要點總結診斷結果。


步驟 5 — 產生內容

根據所選的群組,產生以下其中一種內容。完整撰寫——真實的句子、真實的主張,而不是骨架。

針對群組 1:直接比較頁面

結構:

  • H1:「[競爭對手] vs Amplitude:哪個產品分析工具適合您?」(或類似)
  • 頂部的 TL;DR 框(2-3 句):直接回答每個工具最適合誰
  • 概述章節:兩個工具的簡短公平描述
  • 功能比較表:在與目標受眾最相關的 8-12 個維度上並排比較(事件追蹤、會話重播、A/B 測試、定價模式、資料治理等)
  • 何時選擇 [競爭對手]:誠實清單——3-4 個他們更適合的情境
  • 何時選擇 Amplitude:3-4 個情境,附帶特定功能說明
  • 遷移章節(如果相關的話):「從 [競爭對手] 切換?以下是您可以期待的」
  • FAQ 區塊:5 個 Q&A,來自群組 1 的實際提示詞

針對群組 2:替代方案頁面

結構:

  • H1:「[Year] 年最佳 [競爭對手] 替代方案:產品團隊比較」
  • 開場段落:用 2 句話回答核心問題——誰從 [競爭對手] 切換以及為什麼
  • 比較表:前 5-6 個替代方案,附帶關鍵差異點和最適合的說明;Amplitude 列在首位,使用最強的定位
  • 每個替代方案的詳細章節:150-200 字,涵蓋它的優點、缺點以及最適合誰
  • 從 [競爭對手] 遷移:資料可移植性、儀表化變更、學習曲線
  • FAQ 區塊:4-5 個來自群組 2 提示詞的 Q&A

針對群組 3:類別佔領頁面

結構:

  • H1:「[Year] 年最佳 [類別] 工具:產品團隊指南」
  • 開場:直接用 2 句話回答「最好的 X 工具是什麼」
  • 比較表:6-8 個工具,Amplitude 定位在最有價值的用例
  • 每個工具或用例的深入探討章節
  • 如何選擇:包含 4-5 個標準的決策框架
  • FAQ 區塊:5 個來自群組 3 提示詞的 Q&A

中繼欄位(所有頁面類型)

務必包含:

  • metaTitle — 50-60 個字元,關鍵字豐富,比較頁面需包含競爭對手名稱
  • metaDescription — 140-160 個字元,回答核心查詢並包含行動呼籲
  • slug — 確認或建議一個關鍵字優化的 URL 路徑

步驟 6 — 推送到 CMS

使用你在步驟 0 中發現的資訊。這是一個新文件(建立操作,而非更新)。

Sanity — 使用 create_documents_from_markdown,內容為完整的文章內容。設定 _type 以符合部落格/落地頁面結構。如果不確定,詢問用戶:「您 Sanity 結構中比較頁面的文件類型是什麼?」未經明確指示,絕對不要使用 publish_documents。

Contentful — 使用 create_entry,contentType 符合他們的部落格或落地頁面類型。設定 fields.title、fields.slug、fields.body。保持 published: false。

HubSpot — 使用 create_blog_post,state: DRAFT。包含 meta description 和 slug。

WordPress — 使用 wp_create_post,status: draft。將 H1 對應到 title,內容對應到 content。

Ghost — 使用 create_post,status: draft。包含 slug、title、html 或 lexical,以及 meta_description。

Webflow — 使用 create_cms_item,目標是部落格集合。將欄位對應到集合的結構(如果從上下文中不明確,請詢問用戶欄位名稱)。

推送後,確認:「完成——[頁面標題] 已以草稿形式儲存在 [CMS] 中。這是 ID/URL:[連結]。在發布前請在那裡審查。」

始終輸出完整的 Markdown 備份,即使 CMS 推送成功,以便團隊有本地副本。


什麼讓競爭對手內容被引用

AI 模型會引用那些直接、公平且具體地回答比較問題的來源。以下是一些 consistently 翻轉引用的原則:

  • 在第一段回答「哪個比較好」。 不要讓讀者滾動。如果答案是「取決於用例」,就那樣說——並說明哪些用例偏向哪個工具。
  • 公平對待競爭對手。 承認競爭對手優勢的頁面比純粹推廣的內容更被視為值得信賴。說「Mixpanel 非常適合專注於漏斗的行動優先團隊」顯示了權威性。
  • 比較表會被直接擷取。 AI 模型會提取結構化資料。一個標記良好的功能差異表會被逐字引用。
  • 突出且準確地使用競爭對手名稱。 AI 模型需要將查詢與頁面匹配。一個關於「Mixpanel vs Amplitude」的頁面必須自然且重複地使用這兩個名稱。
  • 對應到真實提示詞的 FAQ 區塊。 使用來自 AI Visibility 的確切問題語言。Q 越接近提示詞,A 被引用的可能性就越大。

Individual skills in this repo

This repo contains 20 individual skills — each has its own dedicated page.

amplitude/builder-skills

Performs deep analysis of a specific Amplitude chart to explain trends, anomalies, and likely drivers. Use when a metric looks unusual, investigating a spike or drop, or understanding the "why" behind numbers.

amplitude/builder-skills

Deeply analyze Amplitude dashboards by analyzing key charts, surfacing top areas for concern and takeaways, identify anomalies, then explain changes using customer feedback trends.

amplitude/builder-skills

Designs A/B tests with proper metrics and variants, analyzes running or completed experiments, and interprets results with statistical rigor. Use when setting up experiments, checking experiment status, analyzing results, or making ship decisions.

amplitude/builder-skills

Synthesizes customer feedback into actionable themes including feature requests, bugs, pain points, and praise. Use when planning product roadmap, understanding user sentiment, investigating specific issues, or preparing voice-of-customer reports.

amplitude/builder-skills

Analyze MCP server usage instrumented with Amplitude's MCP Analytics SDK: break usage and errors down by tool, read the rationales within each tool to see what callers are trying to do, and produce a prioritized write-up of actionable fixes. Use this skill whenever the user asks to understand how their MCP server is being used, what agents/users are trying to do with it, why tool calls are failing, what to fix or improve in their MCP server, or asks for an "MCP usage report", "tool error analysis", "intent analysis", "rationale clustering", or "MCP insights". Also trigger when the user mentions [MCP]-prefixed events, tool rationale, tool call errors, or just finished instrumenting their MCP server and wants to see what the data says. Requires the Amplitude MCP connector.

amplitude/builder-skills

Read lost deals and churned accounts from your CRM, extract reasons clustered by theme (missing features, pricing, competitors, UX), and write a prioritized weekly analysis with product improvement recommendations. Use before roadmap planning or to build the case for prioritizing retention work.

amplitude/builder-skills

Creates Amplitude charts from natural language descriptions, handling event selection, filters, groupings, and visualization choices. Use when you know what you want to measure but prefer not to build the chart manually.

amplitude/builder-skills

Guide an Amplitude user through building a custom agent by suggesting use cases grounded in their role and data, shaping the idea into a well-formed spec, and generating a ready-to-run Global Agent deeplink that creates it. Use to create, build, or set up a custom agent, automate a recurring analysis, or put a repeated report on a schedule.

amplitude/builder-skills

Builds comprehensive Amplitude dashboards from requirements or goals, organizing charts into logical sections with appropriate layouts. Use when creating a complete dashboard from scratch or assembling existing charts into a cohesive view.

amplitude/builder-skills

Monitors all active and recently completed experiments across Amplitude projects, triages them by importance, then runs deep analysis and reporting on the most impactful ones. Use when the user asks to "check on experiments", "experiment status", "experiment review", "what experiments are running", or wants a periodic experiment health report.

amplitude/builder-skills

Pull Intercom tickets and Slack support messages from the past 7 days, classify each signal, enrich with CRM data (ARR, plan, renewal), score by customer value and churn risk, and output a tiered priority report saved to Drive. Use when you need a fast, data-driven view of what support signals matter most.

amplitude/builder-skills

Use this skill whenever a user wants to improve existing pages on their website to get cited more by AI models — whether they say "our pages aren't getting cited", "improve this page for AI visibility", "which of our pages should we update", "make this article more cite-worthy", "our competitors are getting cited instead of us", "update our content for AI search", or any variation where the goal is improving an existing asset rather than creating something new. This skill pulls owned pages from AI Visibility, identifies which ones have citation potential but are underperforming, compares them against the external pages that are winning citations on the same topics, and produces section-level rewrites or a full-page update — then pushes the revision to the CMS as a draft. Trigger even if the user just says "help me get cited more" or "why is [competitor] getting cited instead of us".

amplitude/builder-skills

Use this skill whenever a user wants to turn AI Visibility data into published content — whether they say "find content gaps", "what should we write about", "which topics have low visibility", "help me get cited by AI models", "create a blog post from our AI Visibility gaps", "we're losing to competitors on these prompts", or any variation where they want to go from AI visibility weakness to a draft article, landing page, or FAQ. This skill connects directly to Amplitude AI Visibility data (topics, prompts, visibility scores, citations, competitor data, full LLM responses and sources) and produces a publish-ready content brief plus full article draft. If the user mentions CMS (WordPress, Webflow, Contentful, Sanity, HubSpot, Ghost, Shopify), also trigger this skill to push the draft directly. Trigger even if they just say something vague like "what content should we create?" in an AI Visibility context.

amplitude/builder-skills

Use this skill whenever a user wants to test content variants before publishing to find which one will get cited most by AI models — whether they say "which version of this content will perform better", "test this article before we publish", "simulate how AI will respond to this content", "which angle should we use", "generate content variants and pick the winner", "run a simulation before publishing", or any variation where the goal is data-driven content selection rather than gut-feel publishing. This skill takes an identified content opportunity, generates 2–3 distinct variants with different angles or structures, scores them against actual AI model responses from AI Visibility, references the Simulate Changes feature for pre-publish validation, and produces a clear recommendation on which variant to publish — then pushes the winner to CMS. Trigger on any mention of "simulate", "test variants", "which performs better", "A/B content", or "before we publish".

amplitude/builder-skills

Use this skill whenever a user wants to understand which external sources are being cited by AI models on topics relevant to their brand, and wants to create content that will outrank those sources — whether they say "what sources are AI models citing", "why is [third-party site] being cited instead of us", "we want to be the definitive source on X", "build something that gets cited more than G2 or TechRadar", "create an authoritative asset", or any variation where the goal is producing a new reference asset (definition page, benchmark, methodology, glossary, comparison hub) designed to beat existing top-cited sources. This skill analyzes AI Visibility source data, reverse-engineers what makes top-cited pages authoritative, and produces a superior source asset — then pushes it to CMS as a draft. Trigger on any mention of "sources", "third-party citations", "authoritative content", "definitional pages", or "outrank".

amplitude/builder-skills

Instrument a Node/TypeScript MCP server with Amplitude's @amplitude/mcp-analytics SDK so tool calls, sessions, and rationale are tracked as Amplitude events. Use this skill whenever the user wants to add Amplitude analytics to their MCP server, mentions "MCP Analytics", "@amplitude/mcp-analytics", "instrument my MCP server", "track MCP tool calls", "add rationale to my MCP tools", or wants agent traffic (Claude, Cursor, ChatGPT) attributed back to Amplitude. Also use for adding UTM tagging to MCP-returned links, or for troubleshooting identity/user_id mismatches between MCP events and web/mobile Amplitude data.

amplitude/builder-skills

Instruments a pull request with Amplitude analytics that conform to the project's existing taxonomy. Reads the tracking plan via the Amplitude MCP server (events, properties, naming conventions), analyzes the PR diff to find the few user actions genuinely worth tracking, detects the codebase's SDK and tracking patterns, and adds instrumentation that matches both. Optionally (opt-in) stages new events and properties on an Amplitude tracking-plan branch for data-governance review. Use when asked to "instrument this PR", "add analytics to this change", "add tracking", "add Amplitude events", "instrument this feature", or "what should I track here".

amplitude/builder-skills

Diagnoses product health by cross-referencing Amplitude analytics (dashboards, charts, funnels, feedback, AI agent analytics), optionally Datadog (errors, latency, stack traces), and optionally Slack (qualitative feedback, bug reports, feature requests). Identifies what's broken, what's working, and what to do about it — with root causes, not just symptoms. Use when asked to "diagnose my product", "what's going on", "product health check", "what's broken", "where are users struggling", "give me a product diagnosis", or "what should I focus on".

amplitude/builder-skills

Turn one or more meeting transcripts, notes, or Slack threads into concise takeaways and clear action items with DRIs. Works with a single meeting or a batch from the whole week.

amplitude/builder-skills

Summarizes B2B account health by analyzing usage patterns, engagement trends, risk signals, and expansion opportunities. Use for customer success reviews, renewal preparation, QBRs, or account prioritization.

相關技能